Ophthalmic & Physiological Optics ISSN 0275-5408
Seeing pedestrians at night: effect of driver age and visual abilities Joanne M. Wood1, Philippe Lacherez1 and Richard A. Tyrrell2 1
School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Australia, and 2Department of Psychology, Clemson University, Clemson, USA
Citation information: Wood JM, Lacherez P & Tyrrell RA. Seeing pedestrians at night: effect of driver age and visual abilities. Ophthalmic Physiol Opt 2014; 34: 452–458. doi: 10.1111/opo.12139
Keywords: age, motion sensitivity, nighttime driving, pedestrian recognition Correspondence: Joanne M Wood E-mail address: [email protected] Received: 4 January 2014; Accepted: 6 May 2014; Published Online: 2 June 2014
Abstract Purpose: To quantify the effects of driver age on night-time pedestrian conspicuity, and to determine whether individual differences in visual performance can predict drivers’ ability to recognise pedestrians at night. Methods: Participants were 32 visually normal drivers (20 younger: M = 24.4 years 6.4 years; 12 older: M = 72.0 years 5.0 years). Visual performance was measured in a laboratory-based testing session including visual acuity, contrast sensitivity, motion sensitivity and the useful field of view. Nighttime pedestrian recognition distances were recorded while participants drove an instrumented vehicle along a closed road course at night; to increase the workload of drivers, auditory and visual distracter tasks were presented for some of the laps. Pedestrians walked in place, sideways to the oncoming vehicles, and wore either a standard high visibility reflective vest or reflective tape positioned on the movable joints (biological motion). Results: Driver age and pedestrian clothing significantly (p < 0.05) affected the distance at which the drivers first responded to the pedestrians. Older drivers recognised pedestrians at approximately half the distance of the younger drivers and pedestrians were recognised more often and at longer distances when they wore a biological motion reflective clothing configuration than when they wore a reflective vest. Motion sensitivity was an independent predictor of pedestrian recognition distance, even when controlling for driver age. Conclusions: The night-time pedestrian recognition capacity of older drivers was significantly worse than that of younger drivers. The distance at which drivers first recognised pedestrians at night was best predicted by a test of motion sensitivity.
Introduction Older drivers commonly report difficulties with visibility at night, and some report that they are reluctant to drive at night,1–4 presumably because they have more difficulty seeing under low illumination. Crash data suggest that driving at night can be more dangerous than driving during daytime hours; adjusted for distance driven, the fatality rate at night is two to four times higher than that for the daytime.5 An important class of low contrast hazard that might easily be missed under night-time conditions is pedestrians, who unlike most vehicles may not be illuminated. For crashes 452
involving pedestrians, the night-time pedestrian fatality rates are up to seven times higher than those in the daytime.6 Analyses of crash databases indicate that reduced lighting and poor visibility are associated with these relatively high crash rates, rather than other factors that vary between day and night-time, such as driver fatigue and alcohol consumption.6,7 The contribution of vision to the higher night-time crash risk is supported by studies of self-reported night-time driving difficulty and driving cessation. In large cohort studies of older adults, self-restriction of night-time driving was significantly associated with reductions in contrast
© 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists Ophthalmic & Physiological Optics 34 (2014) 452–458
J M Wood et al.
sensitivity (CS) and low contrast visual acuity (VA) in glare.8 Similarly, those with a reduction in CS and visual fields were shown to have a higher likelihood of night-time driving cessation.9 A real-world driving study indicated that reduced luminance impaired the driving recognition ability of both younger and older drivers and that these impairments in performance were better predicted by CS and low luminance VA than by photopic measures of high contrast VA.10 Importantly, the measures of visual function in that study did not assess divided attention (which may be important in determining the capacity of drivers to detect peripheral and less visible road objects), or motion sensitivity (which may determine the capacity to detect the presence of movement from pedestrians or cyclists). The capacity of motion sensitivity in predicting various aspects of driving performance has been demonstrated in a small number of studies including on-road driving performance under closed11 and open road12 conditions, as well as laboratory-based indices of aspects of driving performance.13–15 Many important cues in driving involve visual motion, including detection of hazards that move relative to the visual background, such as bicycles, other vehicles and pedestrians; the coherence (or lack of coherence) among these objects relative to the background is potentially a critical cue for discriminating these hazards from their backgrounds.16–18 The aim of this study was thus to determine the extent to which driver age impacts on drivers’ recognition of pedestrians at night and whether tests of visual function including motion sensitivity and visual attention are better than standard measures of visual performance (e.g. VA and CS) in predicting the distance at which night-time pedestrians are first recognised. Methods Participants Participants included 20 younger (mean age 24.35 6.42 years, range 18–38) and 12 older drivers (mean age 72.00 4.95 years, range 63–80) who were recruited via a number of different methods, including presentations by the research team, recruitment notices placed on university noticeboards (both electronic and physical), participation in previous studies and graduate students. All participants were licensed drivers and satisfied the minimum Australian drivers’ licensing criteria for binocular visual acuity of 6/12 (logMAR +0.30) or better when wearing their habitual optical correction (if any). All participants were na€ıve to the hypotheses under investigation. The study followed the tenets of the Declaration of Helsinki and was approved by the Queensland University of Technology Human Research Ethics Committee. All participants were given a full explanation of the nature and
Night-time pedestrian recognition
possible consequences of the study, and written informed consent was obtained with the option to withdraw from the study at any time. A confidential, pre-experimental questionnaire was administered to obtain a general sense of the driving habits of the participants. Only those findings of relevance to general driving characteristics are reported here. The young participants reported a mean of 7.08 5.77 years of driving experience compared to 52.92 4.46 years for the older participants. When questioned about night-time driving experiences over the previous year, younger participants reported that 45.5% (18.4%) of their driving was undertaken under night-time conditions compared to 12.8% (8.8%) for the older participants. Vision assessment Participants completed a battery of visual tests each of which were conducted binocularly and while wearing their habitual distance correction. Visual acuity Distance high contrast visual acuity was assessed under photopic illumination conditions using a logMAR Bailey Lovie chart at a viewing distance of 3 m and scored on a letter by letter basis. Contrast sensitivity Letter contrast sensitivity was measured using the Pelli-Robson chart under the recommended testing conditions using a letter by letter scoring system and an additional working distance lens.19 Motion sensitivity Central motion sensitivity was measured using a computerbased random dot kinematogram.12 Participants viewed (at a distance of 3.2 m) a field of dots (subtending 3.9° 9 3.9°), within which a smaller (2.9° 9 2.9°) central panel of dots moved coherently in one of four directions (up, down, left or right) over four discrete steps. Participants were instructed to indicate the predominant direction of motion of the central dots. Across trials the extent of the movement (in terms of the displacement of each pixel between frames) was varied in a two-down one-up staircase, with eight reversals. The threshold (Dmin) was defined as the average of the displacement for the last six reversals in the series. Useful field of view Participants completed all three subtests of the commercially available UFOV, which measures visual processing speed for attentional tasks of increasing difficulty.20,21 Subtest 1 (visual processing speed) is a central discrimination
© 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists Ophthalmic & Physiological Optics 34 (2014) 452–458
453
Night-time pedestrian recognition
J M Wood et al.
task, while Subtest 2 (divided attention) consists of the same central discrimination task while the participant is also required to localise a peripheral target presented randomly along one of eight radial spokes. Subtest 3 (selective attention) involves the same tasks as in Subtests 1 and 2 with the addition of visual distracter targets. The outcome measure was given as the target duration (in milliseconds) at which each of the subtests was performed accurately 75% of the time. Driving assessment Testing was conducted on a closed road circuit that has been used in previous studies,22–24 on nights during which there was no active precipitation and all road surfaces were dry. The experimental vehicle was an instrumented righthand drive 1997 Nissan Maxima with automatic transmission and halogen headlights on the low beam setting. A dual-camera parallax-based video measurement system was utilised to determine the distance at which the driver first recognised the presence of a pedestrian, which was recorded by the participant tapping a touch pad.22–24 Eye movements were also recorded while driving around the circuit using the ASL Mobile Eye (Applied Science Technologies, Bedford, MAUSA; www.asleyetracking.com)25; these data will be reported separately in a future publication. Two pedestrians walked in place on the right shoulder of the roadway. One was located at the end of a 400 m straight section of roadway and was termed the ‘primary pedestrian’. To reduce the drivers’ expectation that the pedestrian would always be in a single location, another pedestrian, known as the ‘secondary pedestrian’, was located at a corner at the opposite side of the circuit; data for this pedestrian are not reported due to the limited sight distance available. As the test vehicle approached, the pedestrians walked in place, facing either directly towards or directly away from the roadway. This allowed for the inclusion of natural patterns of motion while ensuring the safety of the pedestrian (by preventing them from entering the roadway). Each pedestrian was equipped with a two-way radio, as was the experimenter in the test vehicle; all communications regarding pedestrian clothing and direction of pedestrian travel was conducted between laps while the experimenter was outside of the vehicle so the participant could not hear the conversations. For each lap the pedestrians wore one of two kinds of clothing included retroreflective materials in configurations that have been shown to enhance pedestrian recognition relative to non-reflectorised clothing.22 In both conditions the primary pedestrian wore a black tracksuit top and bottom and black shoes. For the vest condition, the pedestrian 454
also wore a standard lightweight fluorescent yellow vest with 50 mm wide silver retro-reflective (Scotchliteâ 8910 Silver Fabric, 3M, http://solutions.3m.com.au/wps/portal/ 3M/en_AU/PPE_SafetySolutions_APAC/Safety/Products/ Eleven/) material on the shoulders, front and back in a Ushaped pattern. The biological motion (biomotion) condition featured the same vest with the addition of 50 mm wide silver retro-reflective strips (Scotchliteâ 8910 Silver Fabric, 3M) surrounding the elbows, wrists, ankles, and knees. To reduce expectancy effects and to make the driving task more relevant to everyday driving, distracter tasks were added to two-thirds of the laps. These included auditory and visual distracter tasks which have been used in previous studies.26,27 These tasks required participants to verbally report the sum of pairs of numbers (e.g. ‘2 + 5’) that were presented either visually via a dashboard-mounted monitor or auditorily via a computer speaker. The monitor was positioned on the dashboard just left of the steering wheel. The visual distracters consisted of the simultaneous presentation of pairs of numbers (each digit subtending between 3.5 and 4.8 degrees of visual angle). The auditory stimuli were presented at a comfortable listening level set by each participant using an adaptive technique. Pairs of numbers were presented approximately every 3.5 s. Each participant completed a series of data collection laps that included two clothing 9 (either of two pedestrian orientations) 9 three levels of distraction (non, visual, or auditory)). In addition, an initial (practice) lap familiarised the driver with both the vehicle and the driving circuit. The order of the different combinations of clothing, orientation (either to the left or the right) and distracters was randomised. Examination of the frequencies of randomisation indicated that task order was effectively random across both clothing v25 = 7.1, p = 0.21, and distracter conditions v210 = 14.2, p = 0.17. Three additional laps during which one or both pedestrians were absent were included to further reduce expectancy. Participants were instructed to follow the specified route, to drive at a comfortable speed and to press the dashmounted touch pad (and announce ‘pedestrian!’) as soon as they were confident that they recognised that a pedestrian was present ahead. The outcome measure was the distance at which the participants first recognised the primary pedestrian. Data analysis The mean distance at which the pedestrian was first recognised was analysed using a three-way linear mixed effects model with the factors of Age (with two levels: Young and Old), distracters (with three levels: None, Visual and Auditory) and Clothing (with two levels: Vest and Biomotion),
© 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists Ophthalmic & Physiological Optics 34 (2014) 452–458
J M Wood et al.
Night-time pedestrian recognition
Results Table 1 presents the mean visual function data for the younger and older participants. Although the mean visual acuity for the older group was slightly better than 6/6, it was significantly worse than the mean acuity of the younger group. The mean letter contrast sensitivity and motion sensitivity were also significantly worse for the older group, but differences in performance on the UFOV were significantly slower only for the selective attention subtest, but not for visual processing speed or divided attention subtests. Figure 1 shows the mean pedestrian recognition distances as a function of age group and pedestrian clothing. The mean distance at which the drivers first recognised that a pedestrian was present was 190.3 m collapsed across all drivers, pedestrian clothing and distracter conditions. Overall, the older participants recognised the pedestrians at significantly shorter distances than did the younger participants F1,30 = 33.4, p < 0.001; with the older participants recognising pedestrians at approximately half the distance of the younger participants (129.1 m vs 251.5 m). The clothing manipulation had a significant effect on pedestrian recognition distance (F1,30.95 = 105.77, Table 1. Mean (and standard deviation) scores on tests of visual performance for the younger and older participants
Younger Visual acuity (logMAR) Contrast sensitivity (log units) Motion sensitivity (log min arc) UFOV test 1: Processing speed (ms) UFOV test 2: Divided attention (ms) UFOV test 3: Selective attention (ms)
Older
p-value young vs older drivers
0.20 (0.06) 2.07 (0.10)
0.02 (0.09) 1.91 (0.06)
Seeing pedestrians at night: effect of driver age and visual abilities Joanne M. Wood1, Philippe Lacherez1 and Richard A. Tyrrell2 1
School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Australia, and 2Department of Psychology, Clemson University, Clemson, USA
Citation information: Wood JM, Lacherez P & Tyrrell RA. Seeing pedestrians at night: effect of driver age and visual abilities. Ophthalmic Physiol Opt 2014; 34: 452–458. doi: 10.1111/opo.12139
Keywords: age, motion sensitivity, nighttime driving, pedestrian recognition Correspondence: Joanne M Wood E-mail address: [email protected] Received: 4 January 2014; Accepted: 6 May 2014; Published Online: 2 June 2014
Abstract Purpose: To quantify the effects of driver age on night-time pedestrian conspicuity, and to determine whether individual differences in visual performance can predict drivers’ ability to recognise pedestrians at night. Methods: Participants were 32 visually normal drivers (20 younger: M = 24.4 years 6.4 years; 12 older: M = 72.0 years 5.0 years). Visual performance was measured in a laboratory-based testing session including visual acuity, contrast sensitivity, motion sensitivity and the useful field of view. Nighttime pedestrian recognition distances were recorded while participants drove an instrumented vehicle along a closed road course at night; to increase the workload of drivers, auditory and visual distracter tasks were presented for some of the laps. Pedestrians walked in place, sideways to the oncoming vehicles, and wore either a standard high visibility reflective vest or reflective tape positioned on the movable joints (biological motion). Results: Driver age and pedestrian clothing significantly (p < 0.05) affected the distance at which the drivers first responded to the pedestrians. Older drivers recognised pedestrians at approximately half the distance of the younger drivers and pedestrians were recognised more often and at longer distances when they wore a biological motion reflective clothing configuration than when they wore a reflective vest. Motion sensitivity was an independent predictor of pedestrian recognition distance, even when controlling for driver age. Conclusions: The night-time pedestrian recognition capacity of older drivers was significantly worse than that of younger drivers. The distance at which drivers first recognised pedestrians at night was best predicted by a test of motion sensitivity.
Introduction Older drivers commonly report difficulties with visibility at night, and some report that they are reluctant to drive at night,1–4 presumably because they have more difficulty seeing under low illumination. Crash data suggest that driving at night can be more dangerous than driving during daytime hours; adjusted for distance driven, the fatality rate at night is two to four times higher than that for the daytime.5 An important class of low contrast hazard that might easily be missed under night-time conditions is pedestrians, who unlike most vehicles may not be illuminated. For crashes 452
involving pedestrians, the night-time pedestrian fatality rates are up to seven times higher than those in the daytime.6 Analyses of crash databases indicate that reduced lighting and poor visibility are associated with these relatively high crash rates, rather than other factors that vary between day and night-time, such as driver fatigue and alcohol consumption.6,7 The contribution of vision to the higher night-time crash risk is supported by studies of self-reported night-time driving difficulty and driving cessation. In large cohort studies of older adults, self-restriction of night-time driving was significantly associated with reductions in contrast
© 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists Ophthalmic & Physiological Optics 34 (2014) 452–458
J M Wood et al.
sensitivity (CS) and low contrast visual acuity (VA) in glare.8 Similarly, those with a reduction in CS and visual fields were shown to have a higher likelihood of night-time driving cessation.9 A real-world driving study indicated that reduced luminance impaired the driving recognition ability of both younger and older drivers and that these impairments in performance were better predicted by CS and low luminance VA than by photopic measures of high contrast VA.10 Importantly, the measures of visual function in that study did not assess divided attention (which may be important in determining the capacity of drivers to detect peripheral and less visible road objects), or motion sensitivity (which may determine the capacity to detect the presence of movement from pedestrians or cyclists). The capacity of motion sensitivity in predicting various aspects of driving performance has been demonstrated in a small number of studies including on-road driving performance under closed11 and open road12 conditions, as well as laboratory-based indices of aspects of driving performance.13–15 Many important cues in driving involve visual motion, including detection of hazards that move relative to the visual background, such as bicycles, other vehicles and pedestrians; the coherence (or lack of coherence) among these objects relative to the background is potentially a critical cue for discriminating these hazards from their backgrounds.16–18 The aim of this study was thus to determine the extent to which driver age impacts on drivers’ recognition of pedestrians at night and whether tests of visual function including motion sensitivity and visual attention are better than standard measures of visual performance (e.g. VA and CS) in predicting the distance at which night-time pedestrians are first recognised. Methods Participants Participants included 20 younger (mean age 24.35 6.42 years, range 18–38) and 12 older drivers (mean age 72.00 4.95 years, range 63–80) who were recruited via a number of different methods, including presentations by the research team, recruitment notices placed on university noticeboards (both electronic and physical), participation in previous studies and graduate students. All participants were licensed drivers and satisfied the minimum Australian drivers’ licensing criteria for binocular visual acuity of 6/12 (logMAR +0.30) or better when wearing their habitual optical correction (if any). All participants were na€ıve to the hypotheses under investigation. The study followed the tenets of the Declaration of Helsinki and was approved by the Queensland University of Technology Human Research Ethics Committee. All participants were given a full explanation of the nature and
Night-time pedestrian recognition
possible consequences of the study, and written informed consent was obtained with the option to withdraw from the study at any time. A confidential, pre-experimental questionnaire was administered to obtain a general sense of the driving habits of the participants. Only those findings of relevance to general driving characteristics are reported here. The young participants reported a mean of 7.08 5.77 years of driving experience compared to 52.92 4.46 years for the older participants. When questioned about night-time driving experiences over the previous year, younger participants reported that 45.5% (18.4%) of their driving was undertaken under night-time conditions compared to 12.8% (8.8%) for the older participants. Vision assessment Participants completed a battery of visual tests each of which were conducted binocularly and while wearing their habitual distance correction. Visual acuity Distance high contrast visual acuity was assessed under photopic illumination conditions using a logMAR Bailey Lovie chart at a viewing distance of 3 m and scored on a letter by letter basis. Contrast sensitivity Letter contrast sensitivity was measured using the Pelli-Robson chart under the recommended testing conditions using a letter by letter scoring system and an additional working distance lens.19 Motion sensitivity Central motion sensitivity was measured using a computerbased random dot kinematogram.12 Participants viewed (at a distance of 3.2 m) a field of dots (subtending 3.9° 9 3.9°), within which a smaller (2.9° 9 2.9°) central panel of dots moved coherently in one of four directions (up, down, left or right) over four discrete steps. Participants were instructed to indicate the predominant direction of motion of the central dots. Across trials the extent of the movement (in terms of the displacement of each pixel between frames) was varied in a two-down one-up staircase, with eight reversals. The threshold (Dmin) was defined as the average of the displacement for the last six reversals in the series. Useful field of view Participants completed all three subtests of the commercially available UFOV, which measures visual processing speed for attentional tasks of increasing difficulty.20,21 Subtest 1 (visual processing speed) is a central discrimination
© 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists Ophthalmic & Physiological Optics 34 (2014) 452–458
453
Night-time pedestrian recognition
J M Wood et al.
task, while Subtest 2 (divided attention) consists of the same central discrimination task while the participant is also required to localise a peripheral target presented randomly along one of eight radial spokes. Subtest 3 (selective attention) involves the same tasks as in Subtests 1 and 2 with the addition of visual distracter targets. The outcome measure was given as the target duration (in milliseconds) at which each of the subtests was performed accurately 75% of the time. Driving assessment Testing was conducted on a closed road circuit that has been used in previous studies,22–24 on nights during which there was no active precipitation and all road surfaces were dry. The experimental vehicle was an instrumented righthand drive 1997 Nissan Maxima with automatic transmission and halogen headlights on the low beam setting. A dual-camera parallax-based video measurement system was utilised to determine the distance at which the driver first recognised the presence of a pedestrian, which was recorded by the participant tapping a touch pad.22–24 Eye movements were also recorded while driving around the circuit using the ASL Mobile Eye (Applied Science Technologies, Bedford, MAUSA; www.asleyetracking.com)25; these data will be reported separately in a future publication. Two pedestrians walked in place on the right shoulder of the roadway. One was located at the end of a 400 m straight section of roadway and was termed the ‘primary pedestrian’. To reduce the drivers’ expectation that the pedestrian would always be in a single location, another pedestrian, known as the ‘secondary pedestrian’, was located at a corner at the opposite side of the circuit; data for this pedestrian are not reported due to the limited sight distance available. As the test vehicle approached, the pedestrians walked in place, facing either directly towards or directly away from the roadway. This allowed for the inclusion of natural patterns of motion while ensuring the safety of the pedestrian (by preventing them from entering the roadway). Each pedestrian was equipped with a two-way radio, as was the experimenter in the test vehicle; all communications regarding pedestrian clothing and direction of pedestrian travel was conducted between laps while the experimenter was outside of the vehicle so the participant could not hear the conversations. For each lap the pedestrians wore one of two kinds of clothing included retroreflective materials in configurations that have been shown to enhance pedestrian recognition relative to non-reflectorised clothing.22 In both conditions the primary pedestrian wore a black tracksuit top and bottom and black shoes. For the vest condition, the pedestrian 454
also wore a standard lightweight fluorescent yellow vest with 50 mm wide silver retro-reflective (Scotchliteâ 8910 Silver Fabric, 3M, http://solutions.3m.com.au/wps/portal/ 3M/en_AU/PPE_SafetySolutions_APAC/Safety/Products/ Eleven/) material on the shoulders, front and back in a Ushaped pattern. The biological motion (biomotion) condition featured the same vest with the addition of 50 mm wide silver retro-reflective strips (Scotchliteâ 8910 Silver Fabric, 3M) surrounding the elbows, wrists, ankles, and knees. To reduce expectancy effects and to make the driving task more relevant to everyday driving, distracter tasks were added to two-thirds of the laps. These included auditory and visual distracter tasks which have been used in previous studies.26,27 These tasks required participants to verbally report the sum of pairs of numbers (e.g. ‘2 + 5’) that were presented either visually via a dashboard-mounted monitor or auditorily via a computer speaker. The monitor was positioned on the dashboard just left of the steering wheel. The visual distracters consisted of the simultaneous presentation of pairs of numbers (each digit subtending between 3.5 and 4.8 degrees of visual angle). The auditory stimuli were presented at a comfortable listening level set by each participant using an adaptive technique. Pairs of numbers were presented approximately every 3.5 s. Each participant completed a series of data collection laps that included two clothing 9 (either of two pedestrian orientations) 9 three levels of distraction (non, visual, or auditory)). In addition, an initial (practice) lap familiarised the driver with both the vehicle and the driving circuit. The order of the different combinations of clothing, orientation (either to the left or the right) and distracters was randomised. Examination of the frequencies of randomisation indicated that task order was effectively random across both clothing v25 = 7.1, p = 0.21, and distracter conditions v210 = 14.2, p = 0.17. Three additional laps during which one or both pedestrians were absent were included to further reduce expectancy. Participants were instructed to follow the specified route, to drive at a comfortable speed and to press the dashmounted touch pad (and announce ‘pedestrian!’) as soon as they were confident that they recognised that a pedestrian was present ahead. The outcome measure was the distance at which the participants first recognised the primary pedestrian. Data analysis The mean distance at which the pedestrian was first recognised was analysed using a three-way linear mixed effects model with the factors of Age (with two levels: Young and Old), distracters (with three levels: None, Visual and Auditory) and Clothing (with two levels: Vest and Biomotion),
© 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists Ophthalmic & Physiological Optics 34 (2014) 452–458
J M Wood et al.
Night-time pedestrian recognition
Results Table 1 presents the mean visual function data for the younger and older participants. Although the mean visual acuity for the older group was slightly better than 6/6, it was significantly worse than the mean acuity of the younger group. The mean letter contrast sensitivity and motion sensitivity were also significantly worse for the older group, but differences in performance on the UFOV were significantly slower only for the selective attention subtest, but not for visual processing speed or divided attention subtests. Figure 1 shows the mean pedestrian recognition distances as a function of age group and pedestrian clothing. The mean distance at which the drivers first recognised that a pedestrian was present was 190.3 m collapsed across all drivers, pedestrian clothing and distracter conditions. Overall, the older participants recognised the pedestrians at significantly shorter distances than did the younger participants F1,30 = 33.4, p < 0.001; with the older participants recognising pedestrians at approximately half the distance of the younger participants (129.1 m vs 251.5 m). The clothing manipulation had a significant effect on pedestrian recognition distance (F1,30.95 = 105.77, Table 1. Mean (and standard deviation) scores on tests of visual performance for the younger and older participants
Younger Visual acuity (logMAR) Contrast sensitivity (log units) Motion sensitivity (log min arc) UFOV test 1: Processing speed (ms) UFOV test 2: Divided attention (ms) UFOV test 3: Selective attention (ms)
Older
p-value young vs older drivers
0.20 (0.06) 2.07 (0.10)
0.02 (0.09) 1.91 (0.06)
